I have a qubo problem with 50 variables. The resulting graph is sparse (each vertex has at most 5 neighbors).
I solved the problem using D-Wave's Simulated Annealing and Kerberos. I also checked the solutions using other solvers and obtained identical results. I have reasons to believe that the solutions are globally optimal.
However, whenever I try using DWaveSampler with EmbeddingComposite the quality of solutions is really poor. Problem inspector does not issue any warnings.
While Ocean tools documentations is absolutely superb, unfortunately I can't make any practical sense of D-Wave systems documentation.
My question is:
How can I tune DWaveSampler so that it produces good solutions?
I was modifying annealing_time but this doesn't seem to affect anything.
Thanks a bunch!